Removing duplicate dataframes in a list

问题

I have a list in python that contains duplicate dataframes. The goal is to remove these duplicate dataframes in whole. Here is some code:

import pandas as pd
import numpy as np
##Creating Dataframes
data1_1 =[[1,2018,80], [2,2018,70]]

data1_2 =  [[1,2017,77], [3,2017,62]]


df1 = pd.DataFrame(data1_1, columns = ['ID', 'Year', 'Score'])
df2 = pd.DataFrame(data1_2, columns = ['ID', 'Year', 'Score'])


###Creating list with duplicates
all_df_list = [df1,df1,df1,df2,df2,df2]

The desired result is this:

###Desired results
desired_list = [df1,df2]

Is there a way to remove any duplicated dataframes within a python list?

Thank you

回答1:

We can use pandas DataFrame.equals with list comprehension in combination with enumerate to compare the items in the list between each other:

desired_list = [all_df_list[x] for x, _ in enumerate(all_df_list) if all_df_list[x].equals(all_df_list[x-1]) is False]

print(desired_list)
[   ID  Year  Score
0   1  2018     80
1   2  2018     70,    ID  Year  Score
0   1  2017     77
1   3  2017     62]

DataFrame.equals returns True if the compared dataframes are equal:

df1.equals(df1)
True

df1.equals(df2)
False

Note As Wen-Ben noted in the comments. Your list should be sorted like [df1, df1, df1, df2, df2, df2]. Or with more df's: [df1, df1, df2, df2, df3, df3]

回答2:

I am doing with numpy.unique

_,idx=np.unique(np.array([x.values for x in all_df_list]),axis=0,return_index=True)
desired_list=[all_df_list[x] for  x in idx ]
desired_list
Out[829]: 
[   ID  Year  Score
 0   1  2017     77
 1   3  2017     62,    ID  Year  Score
 0   1  2018     80
 1   2  2018     70]

回答3:

My first thought was to use a set, but dataframes are mutable and thus not hashable. Do you still need individual dataframes in your list, or is it useful to merge all of these into a single dataframe with all unique values?

You can pd.merge() them all into a single dataframe with unique values using reduce from functools:

from functools import reduce
reduced_df = reduce(lambda left, right: pd.merge(left, right, on=None, how='outer'),
                    all_df_list)
print(reduced_df)
#    ID  Year  Score
# 0   1  2018     80
# 1   2  2018     70
# 2   1  2017     77
# 3   3  2017     62

回答4:

You just need to pass the list of duplicate df's to pd.Series and drop duplicate and convert it back to list

In [229]: desired_list = pd.Series(all_df_list).drop_duplicates().tolist()

In [230]: desired_list
Out[230]:
[   ID  Year  Score
 0   1  2018     80
 1   2  2018     70,    ID  Year  Score
 0   1  2017     77
 1   3  2017     62]

The final desired_list hold 2 dataframe equal to df1, df2

In [231]: desired_list[0] == df1
Out[231]:
     ID  Year  Score
0  True  True   True
1  True  True   True

In [232]: desired_list[1] == df2
Out[232]:
     ID  Year  Score
0  True  True   True
1  True  True   True

来源：https://stackoverflow.com/questions/55735009/removing-duplicate-dataframes-in-a-list

标签

python

pandas

dataframe

duplicates